AI Tips for 1Ls

Talking points for orientation sessions and 1L AI-introduction events. Designed as a presenter’s guide for in-person delivery rather than independent reading. Pairs with the longer 1L Guidance on AI Use.

The headline caveat

Course-specific rules control. General Project guidance does not override a syllabus, assignment instruction, exam rule, clinic rule, journal rule, or supervisor instruction. When in doubt, ask the professor before using AI.

How generative AI works

LLMs like Claude, ChatGPT, and Gemini predict likely text from prompts and training patterns. They are not retrieving verified legal truth. They can produce fluent, useful answers and fluent, wrong answers.

Implications worth flagging:

• AI is useful when the job involves language, organization, variation, or practice.
• AI is risky when the job requires exact legal authority, citations, quotations, or professor-specific course coverage.
• AI can organize material you provide, but you still need to verify that the output reflects the material accurately.
• AI can quiz you on your own notes, but you should check the questions and answers against the assigned materials.

The overreliance problem

Overreliance short-circuits the practice that builds legal judgment. Students need to learn to read cases, identify legally relevant facts, reason by analogy, and work through ambiguity before outsourcing those tasks.

Three rules of thumb:

• Read and make sense of cases yourself first.
• Use AI for tasks where you can judge whether the output is good.
• Use the human-AI-human workflow: your reasoning first, AI to refine or test, you to verify.

Bias

AI can reproduce biased assumptions from its training data. That matters when working in doctrinal areas where race, gender, immigration status, disability, class, or policing affect legal outcomes. Check outputs for stereotyped framing before relying on them.

Confidentiality

Do not paste another person’s work, confidential facts, client or clinic information, class recordings, exam materials, or anything you would not want treated as uploaded data unless your professor has expressly authorized that use and the tool is approved for that material. Current tool-access and data-handling guidance is in the AI Resources Portal.

Academic integrity

Misrepresenting AI use violates academic-integrity rules. Failing to verify or critically assess AI output is your own quality problem, and depending on the assignment, it can become an integrity issue if the work is presented as your independent analysis.

Always check the syllabus. When in doubt, ask.

Suggested uses

Study practice. Ask for questions, hypos, flashcards, or explanations after you have done the reading.

Outline support. Ask AI to organize your own notes or identify gaps in your outline.

Brainstorming. Generate possible paper topics, counterarguments, or alternative structures when the course permits it.

Copyediting. Ask for grammar, clarity, or tone feedback when permitted. Check that the model has not changed the substance.

Prompting matters

Good prompting can turn a generic answer into useful practice:

• Be specific.
• Provide context.
• Say what you have already done.
• Ask for questions before answers.
• Ask the model to identify uncertainty.
• Specify the format.

When the chat goes off the rails

If a long chat starts ignoring instructions, drifting from the course materials, or giving overconfident answers, start a new chat. Shorter, focused conversations are often better for studying.

Status

Maintained for the Penn Carey Law community. Pairs with the longer 1L Guidance on AI Use.